Efficient distributed maximum matching for solving the container exchange problem in the maritime industry

Shao, Fei; Ho, Li-Yung; Wu, Jan‐Jan; Liu, Pangfeng

doi:10.1109/bigdata.2015.7363856

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Big Data Analytics In the Maritime Industry1

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Cited by 3 publications

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“…On the contrary, studies are comparatively rare in the maritime commercial use of big data analytics (Lambrou, 2016). Shao et al (2015) converted the empty container exchange problem to a maximum matching problem in a large general graph and proposed a distributed matching algorithm to solve the problem by mining the container shipment data. Hao et al (2015) introduced the maritime applications of big data analytics and industrial internet of things in Northwest Norway.…”

Section: Big Data Analytics In the Maritime Industrymentioning

confidence: 99%

Value-based optimization of maritime logistics and supply chain

Zhang¹

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Section: Big Data Analytics In the Maritime Industrymentioning

confidence: 99%

Value-based optimization of maritime logistics and supply chain

Zhang¹

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The Global Impact of Container Inventory Imbalance and the Factors that Influence Container Inventory Management Strategies

2016

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Smart Container Inventory Management: A Conceptual Approach

Edirisinghe

2017

CINEC Acad. J.

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Containerization has provided a substantial contribution to the global supply chain. However, it is quite a paradox to note that carriers do not practice or pursue a standard container inventory management system. Each individual carrier develops an inventory management mechanism that suits to their vision, mission, and objectives. These practices are hardly shared between carriers and most of them believe that container inventory management is purely the tacit knowledge of their container controllers and nothing to argue on their decisions. This attitude impedes the industry gaining the experience curve advantage and learning by mistakes. Therefore, the same mistake tends to take place quite often which is highly absurd. The paper challenges this reality and recommends a realistic approach to manage the container inventories of carriers that help reduce global container inventory imbalance. The conceptual model comprises Multidimensional carrier index and country index; 3F Container Inventory Management conceptual model; 6R container supply model; and Virtual container pool.

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Efficient distributed maximum matching for solving the container exchange problem in the maritime industry

Cited by 3 publications

References 20 publications

Value-based optimization of maritime logistics and supply chain

Value-based optimization of maritime logistics and supply chain

The Global Impact of Container Inventory Imbalance and the Factors that Influence Container Inventory Management Strategies

Smart Container Inventory Management: A Conceptual Approach

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